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X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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DTSTART:20240101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251202T140000
DTEND;TZID=Asia/Hong_Kong:20251202T150000
DTSTAMP:20260510T191810
CREATED:20251113T062320Z
LAST-MODIFIED:20251126T063144Z
UID:113888-1764684000-1764687600@ece.hku.hk
SUMMARY:Seminar on Bi-Static Sensing for Next Generation Perceptive Communication Networks: Technologies and Applications
DESCRIPTION:The event time has been revised to start at 2:00 pm. \nAbstract\nIntegrated Sensing and Communications (ISAC) represents a paradigm shift from conventional communication-only networks toward systems that natively integrate radar-like sensing capabilities. It has become a foundational technology for next-generation wireless systems\, including Wi-Fi and 6G networks. \nBi-static sensing\, where a sensing receiver exploits signals transmitted by another node\, naturally aligns with the topology of communication networks. It circumvents the stringent full-duplex requirements of mono-static sensing and offers enhanced spatial sensing diversity. However\, clock (Local oscillating signal) asynchronism\, which inherently exists among spatially separated communication nodes\, poses a central and challenging problem. It can cause ranging ambiguities and disrupt coherent processing of discontinuous measurements\, such as those required for Doppler frequency estimation. If effectively resolved\, sensing could be seamlessly realised within existing communication infrastructures\, requiring minimal hardware or architectural modifications. \nThis talk explores advanced techniques for tackling clock asynchronism in bi-static sensing\, with a focus on efficient single-receiver-based solutions. The problem will first be introduced in the context of 6G perceptive mobile networks\, followed by a comprehensive overview of recent methods applicable to both multi-antenna and single-antenna configurations. I will then present our latest sensing applications developed using these techniques\, including moving-object tracking\, respiration and heartbeat monitoring\, behavior recognition\, and environmental sensing such as rainfall and water-level detection. The talk concludes by outlining key open challenges and future research directions in this rapidly evolving field. \nSpeaker\nProf. Andrew ZHANG\nUniversity of Technology Sydney \nSpeaker’s Biography\nProf. J. Andrew ZHANG (M’04-SM’11) is a Professor in the School of Electrical and Data Engineering\, University of Technology Sydney\, Australia. His research interests are in the area of signal processing for wireless communications and sensing. He has published more than 300 papers in leading Journals and conference proceedings\, and has won 7 best paper awards. He is a recipient of CSIRO Chairman’s Medal and the Australian Engineering Innovation Award for exceptional research achievements in multi-gigabit wireless communications. He is one of the pioneer researchers in ISAC. He initiated the concept of perceptive mobile network in 2017. Since then\, his team has published more than 70 top-tier journal papers on ISAC\, including several highly cited and review articles. In this field\, he has led or participated in multiple research projects with a total value of over AUD 8 million\, established a Joint Laboratory on Network Sensing with a mobile network operator\, developed multiple real-time ISAC demonstration systems\, and is currently advancing their commercialisation. Prof. Zhang co-organised a number of ISAC workshops at leading conferences and special issues in leading IEEE journals. He has also delivered multiple ISAC tutorials and numerous keynotes and invited talks. For details\, please refer to Prof. Zhang’s profile page: https://sites.google.com/view/andrewzhang \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20251202-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/11/1280-7.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251205T110000
DTEND;TZID=Asia/Hong_Kong:20251205T120000
DTSTAMP:20260510T191810
CREATED:20251118T074008Z
LAST-MODIFIED:20251118T083942Z
UID:113926-1764932400-1764936000@ece.hku.hk
SUMMARY:Seminar on 40 Years of Proton Magnetic Resonance Spectroscopy in Human Brain
DESCRIPTION:Abstract\nThe development of whole-body MRI scanners in the late 1980s at field strengths of 1.5T\, together with other fundamental technological advances such shielded field gradients and single-shot spatial localization techniques\, enabled the non-invasive collection of spectra from the human in just a few minutes of scan time. Since that time\, there have been many technical advances and clinical studies performed\, and it remains an active area of research and development. This presentation will review key technical developments including spatial localization techniques for both single voxel spectroscopy and spectroscopic imaging\, spectral analysis\, spectral editing\, and the effects of increasing magnetic field strength. In addition\, the metabolic information from in vivo MRS will be discussed\, including metabolic changes that can be detected in various pathological states\, and applications in the clinic. Finally\, some of the challenges facing the clinical use of MRS and sustainability will be discussed. \nSpeaker\nProf. Peter BARKER\nDirector of Division of MR Research\nJohn Hopkins University School of Medicine \nSpeaker’s Biography\nPeter BARKER\, D.Phil.\, is a Professor of Radiology and Oncology\, and Director of the Division of MR Research at the Johns Hopkins University School of Medicine in Baltimore\, Maryland. He holds a D.Phil. degree in Physical Chemistry from Oxford University.  Since 1989\, he has been a faculty member of the Russell H. Morgan Department of Radiology and Radiological Science at Johns Hopkins\, where his primary interest has been the development of proton MR spectroscopy\, and other MRI techniques\, for applications in the human brain. He has published over 315 original\, peer-reviewed articles\, more than 45 commentaries\, review articles and book chapters\, as well as 3 books on Clinical MR Neuroimaging\, Spectroscopy and Perfusion Imaging. Dr Barker is a fellow of the ISMRM society\, and an editor for the journals Magnetic Resonance in Medicine and NMR in Biomedicine. \nOrganiser\nProf. Ed Xuekui WU\nChair of Biomedical Engineering\,\nLam Woo Professorship in Biomedical Engineering\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20251205-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251208T140000
DTEND;TZID=Asia/Hong_Kong:20251208T150000
DTSTAMP:20260510T191810
CREATED:20251121T085327Z
LAST-MODIFIED:20251121T094034Z
UID:114160-1765202400-1765206000@ece.hku.hk
SUMMARY:Seminar on Semiconductor Nanodimer as a Partially Open Terahertz Resonator
DESCRIPTION:The event has been rescheduled to December 8\, 2025 (Monday). \nAbstract\nResonators are often the first apparatus to be constructed and thoroughly investigated when a new region of the spectrum is being explored. From the days of spark-gap generators in early radio transmission to the more recent maser and laser era\, resonant systems have always been essential in enabling a given range of the spectrum to become accessible to electronic communication and instrument applications. With the current interest in terahertz technology\, it would appear logical to search for structures or physical processes that exhibit natural resonances in the terahertz range. Plasma resonance in extrinsic semiconductors can be designed to exhibit field concentration and guiding characteristics that are impetus for sensing and circuitry applications for research and development of terahertz technology. While a single semiconductor nanoparticle (SNP) does exhibit surface plasmon resonance\, the local terahertz field garnered near the two poles of an SNP lacks symmetry and is strongly influenced by the embedding medium. On the other hand\, a semiconductor nanodimer (SND) formed by two SNPs with a gap in between them offers a more secluded environment for field enhancement with better symmetry in field distribution. Considerable attention has been given to metallic nanodimers\, leading to their roles in sensing and antenna applications. On the other hand\, investigations on SNP and SND are currently in the early stage. The salient characteristics of SNDs formed with matched and dissimilar SNPs are discussed in light of their potential for terahertz components and systems development. \nSpeaker\nProf. Thomas WONG\nProfessor Emeritus\,\nDepartment of Electrical and Computer Engineering\,\nIllinois Institute of Technology\nAdjunct Professor of HKU-EEE \nSpeaker’s Biography\nThomas WONG received the B.Sc. degree from the University of Hong Kong\, and the M.S. and Ph.D. degrees from Northwestern University\, all degrees being in Electrical Engineering. He was a Product Engineer at Motorola Semiconductor (HK) before going to the United States for graduate study. He joined Illinois Institute of Technology as a faculty member in 1981 and is currently a Professor Emeritus in the Electrical and Computer Engineering (ECE) Department. He has conducted research in material measurements\, charge transport in ionic and electronic conductors\, transient electromagnetics\, millimeter-wave communication systems\, and propagation effects in high-speed semiconductor devices. In collaboration with Argonne National Laboratory and Fermilab\, he has contributed to research in dielectric loaded accelerators\, coupler design for superconducting multicell cavity resonators\, and nanoscale position sensors. Recent activities have been on space-charge interactions in semiconductor nanostructures. He has served as Graduate Program Director and Department Chair of the ECE Department. In the 1998-1999 academic year he served as the Chair of the University Faculty Council. He is the author of Fundamentals of Distributed Amplification (Artech 1993) and coauthor of Electromagnetic Fields and Waves (Higher Education Press\, 2002 and 2006). He is a Fellow of the International Association of Advanced Materials. \nOrganiser\nIr Dr. King Hang LAM\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20251208-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/11/1280-6.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251213T140000
DTEND;TZID=Asia/Hong_Kong:20251213T171000
DTSTAMP:20260510T191810
CREATED:20250808T010012Z
LAST-MODIFIED:20251208T021345Z
UID:114346-1765634400-1765645800@ece.hku.hk
SUMMARY:HKU-KAUST Joint Postgraduate Workshop on Computational Imaging 2025
DESCRIPTION:All EEE postgraduate (TPg & RPg) students are welcome! \nThe upcoming “HKU-KAUST Joint Postgraduate Workshop on Computational Imaging 2025” will be held on December 13\, 2025\, organised by the Computational Imaging & Mixed Representation Laboratory. The workshop aims to encourage innovative spirit\, promote excellence and sustain quality\, strive for improvement\, and connect communities. For details of the workshop and speakers\, please visit the event website: https://hku.welight.fun/events/workshop_25Dec \nCoffee\, tea\, and a reception will be provided. \n \nMC\nProf. Evan Y. PENG\, HKU EEE x CS \nCoordinators\nDr. Xin Liu @ HKU; Dr. Qiang Fu @ KAUST \nSpeakers/Guests\n\nWolfgang HEIDRICH\, King Abdullah University of Science and Technology & The University of Hong Kong\nYuhui LIU\, The University of Hong Kong\nNajia SHARMIN\, The University of Hong Kong\nQiang FU\, King Abdullah University of Science and Technology\nErqian DONG\, The University of Hong Kong\nChutian WANG\, The University of Hong Kong\nJiankai XING\, Tsinghua University\nKaixuan WEI\, King Abdullah University of Science and Technology\nZhenyang LI\, The University of Hong Kong\nShi MAO\, King Abdullah University of Science and Technology\nYanmin ZHU\, The University of Hong Kong\nWenbin ZHOU\, The University of Hong Kong
URL:https://ece.hku.hk/events/20251213-1/
LOCATION:Room 602\, Student Commons 6/F\, Pacific Plaza (Off-campus)\, Hong Kong SAR
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/12/1280-2.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251214T133000
DTEND;TZID=Asia/Hong_Kong:20251214T180000
DTSTAMP:20260510T191810
CREATED:20251211T093001Z
LAST-MODIFIED:20251211T093001Z
UID:114399-1765719000-1765735200@ece.hku.hk
SUMMARY:ACM SIGGRAPH Asia 2025 Pre-Conference Technical Workshop
DESCRIPTION:Click HERE to view the details.
URL:https://ece.hku.hk/events/20251214-1/
LOCATION:Room CPD-2.42\, 2/F\, The Jockey Club Tower\, Centennial Campus\, HKU
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/12/3232.jpg
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251216T141500
DTEND;TZID=Asia/Hong_Kong:20251216T151500
DTSTAMP:20260510T191810
CREATED:20251213T025301Z
LAST-MODIFIED:20251213T025434Z
UID:114410-1765894500-1765898100@ece.hku.hk
SUMMARY:Seminar on Developing Value-driven AI: Building Large Language Models with Social Good Principles
DESCRIPTION:Abstract\nThis talk highlights the critical need and urgency for academic communities to advance artificial intelligence (AI) with a focus on value-driven and socially-beneficial LLMs. The presentation is structured in two parts. First\, I will briefly outline my academic and research background\, our vision for AI for Social Good\, and key contributions from over a decade of work in this field. The second part will focus on the development of a large language model (LLM) system embedded with social good principles. As LLMs\, like ChatGPT\, become integral to daily life\, understanding and addressing their ethical and social implications is paramount. This talk explores how implicit values in AI systems can be identified and reshaped using techniques such as fine-tuning and data generation to align with inclusive\, responsible\, and ethical standards. By embedding societal values into LLM design\, this work aims to foster AI systems that promote fairness\, accountability\, and positive societal impact. The significance of this talk lies in its potential to inspire HKU to prioritize ethical AI development\, shaping a future where AI serves as an accelerator for social good. \nSpeaker\nProf. Jacqueline C.K. LAM\nAssociate Professor\,\nDepartment of Electrical and Electronic Engineering (EEE)\,\nThe University of Hong Kong (HKU) \nSpeaker’s Biography\nProf. Jacqueline C.K. LAM is an Associate Professor in the Department of Electrical and Electronic Engineering (EEE) at The University of Hong Kong (HKU)\, where she co-leads the HKU-AI to Advance Well-being and Society Research Lab. With a PhD in Environmental Management from HKU’s Faculty of Architecture (2008)\, she earned a competitive university-wide Research Assistant Professorship based in EEE\, HKU in 2011\, enabling her to pursue interdisciplinary research integrating data science\, social sciences\, neuroscience\, and ethics. Prof. Lam champions AI for Social Good (AIfSG)\, her research places priority on addressing societal challenges\, particularly in air pollution\, asthma and Alzheimer’s disease\, emphasizing fairness\, explainability\, through big data and AIfSG technologies. \nProf. Lam co-leads projects that secured four consecutive U.S. National Academy of Medicine Healthy Longevity Catalyst Awards (2021–2024) with Prof. Victor O.K. Li\, advancing AI-driven early diagnosis and drug discovery for Alzheimer’s disease. She co-leads in Co-PI capacity a 50M HKD RGC Theme-based Research Grant for smart air pollution monitoring and health management\, and a 3.25M HKD RGC-SPPR grant in 2011 for cross-border nuclear safety governance\, reflecting her dedication to impactful\, collaborative socially-beneficial research. \nShe cherishes her international collaborations\, including roles as Visiting Senior Research Fellow at the University of Cambridge’s Judge Business School (since 2013)\, Visiting Fellow at Hughes Hall\, and Visiting Academic at the Department of Computer Science and Technology at Cambridge. Prof. Lam a Visiting Scholar at MIT’s Centre for Energy and Environmental Policy Research and MIT EECS in 2019. In collaboration with Prof. Jon Crowcroft\, FRS. At Cambridge\, they have co-organized five AIfSG symposiums since 2018\, fostering global academic dialogue in value-driven AI research. \nIn teaching\, Prof. Lam is committed to mentoring PhD students at HKU\, nurturing innovative thinkers in AIfSG. She co-established the pioneering HKU-Cambridge PhD Pathway\, enabling engineering students to pursue an MPhil in Technology Policy at Cambridge Judge Business School\, and pioneered interdisciplinary courses on Climate Change and Sustainability (2013–2020) and Deep Learning and Applications (2019-2025). As Area Editor of the Cambridge University Press journal Data and Policy\, she contributes to global discussions on value-driven data policy. Her publications span multiple disciplines\, including IEEE Transactions\, Nature Scientific Reports\, Nature Molecular Psychiatry\, Journal of Alzheimer’s Disease\, Environment International\, Applied Energy\, Energy Policy\, and Data and Policy. Co-directing the HKU-AI WiSe and three HKU-Cambridge AI Research Platforms\, Prof. Lam humbly seeks to advance AIfSG. \nAll are welcome!
URL:https://ece.hku.hk/events/20251216-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251217T100000
DTEND;TZID=Asia/Hong_Kong:20251217T110000
DTSTAMP:20260510T191810
CREATED:20251215T071917Z
LAST-MODIFIED:20251215T072002Z
UID:114421-1765965600-1765969200@ece.hku.hk
SUMMARY:Seminar on Efficient Generative Modelling\, Multi-agent Systems Based on Knowledge Graphs and LLMs
DESCRIPTION:Abstract\nI will overview our recent results on diffusion generative modelling and how to make inference faster\, just in a few steps; also\, I will provide some new concepts of Engineering AI and discuss how we can construct efficient multi-agent systems based on knowledge graphs and LLMs to solve complex engineering problems. \nSpeaker\nProf. Evgeny BURNAEV\nVice President for AI Development & Professor\,\nSkolkovo Institute of Science and Technology\nVisiting Chair Professor\,\nHarbin Institute of Technology \nSpeaker’s Biography\nEvgeny BURNAEV is Vice President for AI Development and Professor at the Skolkovo Institute of Science and Technology (Skoltech)\, where he also directs the Skoltech AI Center. His research focuses on engineering AI\, generative modelling\, optimal transport\, physics-informed machine learning\, and topological data analysis for reliable\, efficient\, and interpretable AI systems. At the AI Center\, Burnaev leads interdisciplinary projects that bridge theoretical foundations and large-scale applications in energy\, transport\, materials\, and climate modelling. \nHe has authored more than 200 peer-reviewed publications in leading international venues (NeurIPS\, ICML\, ICLR\, IEEE\, Nature Scientific Reports) and collaborates with global industry leaders such as Sber\, Huawei\, and Gazprom Neft. His achievements have been recognised with the Russian Government Prize in Science and Technology (2024)\, the Sber Science Award (2024)\, and inclusion in the Elsevier–Stanford global Top-2% scientists list (2023–2025). He also serves as Visiting Chair Professor at the Harbin Institute of Technology and contributes to international expert communities and program committees advancing transparent and trustworthy AI worldwide. \nOrganiser\nProf. Ngai WONG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20251217-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
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BEGIN:VEVENT
DTSTART;TZID=Asia/Hong_Kong:20251219T150000
DTEND;TZID=Asia/Hong_Kong:20251219T163000
DTSTAMP:20260510T191810
CREATED:20251216T014340Z
LAST-MODIFIED:20251216T014340Z
UID:114428-1766156400-1766161800@ece.hku.hk
SUMMARY:Seminar on An Update on Machine Learning for Communication Networks
DESCRIPTION:Abstract\nThe speaker aims to provide an update on recent progress by his research team on machine learning for communication networks. If time permits\, he will also highlight his work on distributed quantum computing and quantum machine learning. \nEfficient allocation of limited resources to competing demands is a crucial issue in the design and management of communication networks. In this seminar\, the speaker will first introduce a new reinforcement-learning (RL) technique for achieving optimal resource allocation in networks with periodic traffic patterns. The effectiveness of this method will be demonstrated through numerical examples. \nIn addition\, a new RL technique will be presented that separates representation learning from RL to enable fully decentralised learning in partially observable multi-agent settings. The approach relies on learned beliefs over the underlying system state. A belief model is first trained by using complete environment information\, which is then used by a state-based RL algorithm using distributed\, local observations only. A set of partially observable environments is constructed\, and the efficacy of this new approach is shown and compared to relevant benchmarks. \nIf time permits\, the speaker will also highlight his recent work on distributed quantum computing and quantum machine learning. \nSpeaker\nProf. Kin K. LEUNG\nDepartment of Electrical and Electronic Engineering\,\nDepartment of Computing\,\nImperial College\, London \nSpeaker’s Biography\nKin K. LEUNG received his B.S. degree from the Chinese University of Hong Kong\, and the M.S. and Ph.D. degrees from University of California\, Los Angeles. He worked at AT&T Bell Labs and its successor companies in New Jersey from 1986 to 2004. Since then\, he has been the Tanaka Chair Professor at Imperial College in London. He was the Head of Communications and Signal Processing Group from 2019 to 2024 and now serves as Co-Director of the School of Convergence Science: Space\, Security and Telecommunications at Imperial. His current research focuses on optimisation and machine learning for design and control of large-scale communications\, computer and quantum networks. He also works on multi-antenna and cross-layer designs for wireless networks. \nHe is a Fellow of the Royal Academy of Engineering\, IEEE Fellow\, IET Fellow\, and member of Academia Europaea. He received the Distinguished Member of Technical Staff Award from AT&T Bell Labs (1994) and the Royal Society Wolfson Research Merits Award (2004-09). Jointly with his collaborators\, he received the IEEE Communications Society (ComSoc) Leonard G. Abraham Prize (2021)\, the IEEE ComSoc Best Survey Paper Award (2022)\, the U.S.–UK Science and Technology Stocktake Award (2021)\, the Lanchester Prize Honorable Mention Award (1997)\, and several best conference paper awards. He chaired the IEEE Fellow Evaluation Committee for ComSoc (2012-15) and served as the General Chair of the IEEE INFOCOM 2025. He has served as an editor for 10 IEEE and ACM journals and chaired the Steering Committee for the IEEE Transactions on Mobile Computing. Currently\, he is an editor for the ACM Computing Survey and International Journal of Sensor Networks. \nOrganiser\nProf. Kaibin HUANG\nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong\n\nAll are welcome!
URL:https://ece.hku.hk/events/20251219-1/
LOCATION:Room CB-603\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=image/jpeg:https://ece.hku.hk/wp-content/uploads/2025/12/1280-6.jpg
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